• Title/Summary/Keyword: Real-time review

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Estimation of Economic Effects on Overseas Oil and Gas E&P by Macroeconomic Model of Korea (거시경제모형을 이용한 해외석유가스개발사업의 경제적 효과 추정 연구)

  • Kim, Ji-Whan;Chung, Woo Jin;Kim, Yoon Kyung
    • Environmental and Resource Economics Review
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    • v.23 no.1
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    • pp.133-156
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    • 2014
  • In general, quantity results of empirical analysis using model shows how much big performance policy has. Therefore this is useful to evaluate a policy. This paper composed macro economic model based on Bank of Korea's quarterly model and annual model, that estimates performance of overseas oil and gas development project to Korean economy in aspect of quantity. In this model, we estimated each effect in real GDP, current account, unemployment rate, CPI and exchange rate carried by recovered amount from overseas oil and gas development project. The recovered amount was evaluated in currency coming from oil and gas acquired from overseas oil and gas development project. Macro economic model of this paper benchmarked macro model composed by Bank of Korea(1997, 2004, 2012). We reviewed model robustness using statistical suitability of each equation and historical simulation for from 1994 to 2011. The recovered amount of overseas oil and gas development project has positive effect in every macro economic index except CPI and exchange rate. Economic effect to macro economic index become bigger with time because the recovered amount of overseas oil and gas development project are increasing until now. Although empirical results of economic effects in every year from the recovered amount of overseas oil and gas development project are different, as of 2011, empirical results showed that the recovered amount of overseas oil and gas development project increase 2.226% and 0.401% in current account and real GDP respectively. And it also decrease 0.489%p in unemployment rate. Exchange rate to US dollars also decrease in amount of 0.379%.

Design and Analysis of Ubiquitous Social Network Management Service Model: u-Recruiting Service Model (유비쿼터스 사회연결망관리 서비스 모델 설계 및 분석: u-구인 구직 서비스 모델을 중심으로)

  • Oh, Jae-Suhp;Lee, Kyoung-Jun;Kim, Jae-Kyeong
    • Information Systems Review
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    • v.13 no.1
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    • pp.33-59
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    • 2011
  • Although online social network services widely used in human networking and recruiting industries, it is showing off its limitations in followings-it's hard to reach the status of seamless connection between offline and online; the incompletion and low credibility of the information came from non-face-to-face profile exchange; and the restraint of user autonomy due to centralized control. This paper defines the ubiquitous social network management which enables the seamless real-time face-to-face social interactions of the users based on WPAN (Wireless Personal Area Network) who share the same interest in real word and deduces a ubiquitous social network management framework based on it. As an instance of ubiquitous social network management, u-Recruiting service model will be designed and analyzed. The Analysis using the business model will be followed by the possible scenario of service model. The role, value proposition and potential benefits of the each participants in this service model and will be given as well. In order to evaluate relative advantages of the model suggested by this study, 6 cases will be compared.

A Study on the Method of Energy Evaluation in Water Supply Networks (상수관망의 에너지 평가기법에 관한 연구)

  • Kim, Seong-Won;Kim, Dohwan;Choi, Doo Yong;Kim, Juhwan
    • Journal of Korea Water Resources Association
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    • v.46 no.7
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    • pp.745-754
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    • 2013
  • The systematic analysis and evaluation of required energy in the processes of drinking water production and supply have attracted considerable interest considering the need to overcome electricity shortage and control greenhouse gas emissions. On the basis of a review of existing research results, a practical method is developed in this study for evaluating energy in water supply networks. The proposed method can be applied to real water supply systems. A model based on the proposed method is developed by combining the hydraulic analysis results that are obtained using the EPANET2 software with a mathematical energy model on the MATLAB platform. It is suggested that performance indicators can evaluate the inherent efficiency of water supply facilities as well as their operational efficiency depending on the pipeline layout, pipe condition, and leakage level. The developed model is validated by applying it to virtual and real water supply systems. It is expected that the management of electric power demand on the peak time of water supply and the planning of an energy-efficient water supply system can be effectively achieved by the optimal management of energy by the proposed method in this study.

Effects of the Characteristics of the JooTeakYeonKeum Contract on Its Termination (주택연금의 특성이 계약해지에 미치는 영향)

  • Jeon, You Jeong;Yoo, Seon Jong
    • Korea Real Estate Review
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    • v.28 no.1
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    • pp.115-130
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    • 2018
  • This study investigated the factors influencing the termination of the JooTeakYeonKeum contract according to its rate increase, and aimed to identify the differences in the factors affecting the cancellation of the contract according to the collateralized house price range. The results showed that the higher the cumulative increase rate of the mortgage housing price at the time of subscription is, the higher the monthly payment, the larger the gap between the monthly payment and the minimal living expenses for aging, the lower the net population moving rate in the previous month, and the lower the cumulative mortgage. Moreover, the JooTeakYeonKeum contract is terminated. The factors affecting the termination of the contract are different in each interval of the price range of the mortgage housing. To confirm this, a mortgage price range model was constructed and analyzed. The results showed that 60% of the elderly participants in the JooTeakYeonKeum program subscribed thereto with a below-average subsidized housing price. It was confirmed that the factors affecting the termination of the contract differ by price range. Lowering the risk of increasing the JooTeakYeonKeum termination rate will be a significant way of boosting the welfare of elderly people aged 65 and older, and of easing the impact of population aging.

Digital painting: Image transfonnation, simulation, heterologie and transfonnation (현대회화에서의 형태와 물질 -Digital Transfiguration에 관한 연구-)

  • Jeong, Suk-Yeong
    • Journal of Science of Art and Design
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    • v.10
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    • pp.161-181
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    • 2006
  • The words which appeared in my theoretical study and work are image transformation to digital painting, simulation, heterologie and transfiguration, etc. Firstly, let's look into 'digital era' or 'new media era'. Nowadays, the image world including painting within the rapid social and cultural change, which is called as digital era, is having the dramatic change. Together with the development of scientific technology, large number of events which was deemed to be impossible is happening as real in image world Moreover, these changes in image world is greatly influencing to our life. The word which compresses this change of image world and shows is 'digital'. Digit, which means fingers in Latin, indicates separately changing signal, and to be more narrow, it indicates the continual signal of '0' and ' 1' in computer. The opposite word is 'analogue'. As analogue is the word meaning 'infer' or 'similarity', it indicates the signal or form which continuously changes along the series of time when it is compared to digital. Instead of analogue, digital is embossed as a major ruler along the whole area of our current culture. In whole culture and art area, and in whole generalscience, digital is appearing as it has the modernism and importance. The prefix, 'digital', e.g. digital media, digital culture, digital design, digital philosophy, etc, is treated as the synonym of modernism and something new. This advent of digital results the innovative change to the image world, creates the new beauty experience which we could not experience before, and forecasts the formation of advanced art and expansion of creative area. Various intellectual activities using computer is developing the whole world with making the infrastructure. Computer in painting work immediately accomplishes the idea of painters, takes part in simulation work, contingency such as abrupt reversal, extraction, twisting, shaking, obscureness, overlapping, etc, and timing to stimulate the creativity of painters, and provides digital formative language which enables new visual experience to the audience. When the change of digital era, the image appeared in my work is shown in 'transfiguration' like drawing. The word, 'transfiguration' does not indicate the completed and fixed real substance but indicate endlessly moving and floating shape. Thus, this concept is opposite to the substantial consideration, so that various concepts which is able to replace this in accordance with the similar cases are also exist such as change, deterioration, mutation, deformity of appearance and morphing which is frequently used in computer as a technical word. These concepts are not clearly classified, and variably and complicatedly related. Transfiguration basically means the denial of "objectivity' and '(continual) stagnation' or deviation from those. This phenomenon is appeared through the all art schools of art ever since the realism is denied in the 19th century. It is called as 'deformation' in case of expressionism, futurism, cubism, etc, in the beginning of the century, which its former indication is mostly preserved within the process of structural deviation and which has the realistic limit which should be preserved. On the contrary, dramatic transfiguration which has been showing in the modern era through surrealism is different in the point that dramatic transfiguration tends to show the deterioration and deviation rather than the preservation of indicated object. From this point, transfiguration coming out from morphing using computer deteriorates and hides the reality and furthermore, it replaces the 'reality'. Moreover, transfiguration is closely approached to the world of fake or 'imaginary' simulation world of Baudrillard. According to Baudrillard, the image hides and deteriorates the reality, and furthermore, expresses 'not existing' to 'imaginary' under the name of transfiguration. Certain reality, that is, image which is absent from the reality is created and overflowed, so that it finally replaces the reality. This is simulation as it is said by Baudrillard. In turn, Georges Bataille discusses about the image which is produced by digital technology in terms of heterologie. Image of heterologie is the visual signal which is established with the media. Image of media is to have the continuous characteristics of produce, extinction, and transformation, and its clear boundary between images becomes meaningless. The meaning of composition, excess, violation, etc of digital image is explained to heterological study or heteologie suggested as important meaning of Georges Bataille who is a heretic philosopher. As the form and image of mutation shows the shape in accordance with mechanical production, heterologie is introduced as very low materialism (or bas materialisme), in this theory. Heterologie as low materialism which is gradually changing is developing as a different concept and analysis because of the change of time in the late 20s century beside high or low meaning. Including my image, all images non-standardizes and transforms the code. However, reappearance and non-standardization of this code does not seem to be simple. The problem of transformation caused by transfiguration which appears in my digital drawing painting, simulation, heterologie, etc, are the continual problems. Moreover, the subject such as existence of human being, distance from the real life, politics and social problems are being extended to actual research and various expressing work. Especially, individual image world is established by digital painting transfiguration technique, and its change and review start to have the durability. The consciousness of observers who look at the image is changing the subject. Together with theoretical research, researchers are to establish the first step to approach to various image change of digital era painting through transfiguration technique using our realistic and historical image.

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An Analysis of IT Trends Using Tweet Data (트윗 데이터를 활용한 IT 트렌드 분석)

  • Yi, Jin Baek;Lee, Choong Kwon;Cha, Kyung Jin
    • Journal of Intelligence and Information Systems
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    • v.21 no.1
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    • pp.143-159
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    • 2015
  • Predicting IT trends has been a long and important subject for information systems research. IT trend prediction makes it possible to acknowledge emerging eras of innovation and allocate budgets to prepare against rapidly changing technological trends. Towards the end of each year, various domestic and global organizations predict and announce IT trends for the following year. For example, Gartner Predicts 10 top IT trend during the next year, and these predictions affect IT and industry leaders and organization's basic assumptions about technology and the future of IT, but the accuracy of these reports are difficult to verify. Social media data can be useful tool to verify the accuracy. As social media services have gained in popularity, it is used in a variety of ways, from posting about personal daily life to keeping up to date with news and trends. In the recent years, rates of social media activity in Korea have reached unprecedented levels. Hundreds of millions of users now participate in online social networks and communicate with colleague and friends their opinions and thoughts. In particular, Twitter is currently the major micro blog service, it has an important function named 'tweets' which is to report their current thoughts and actions, comments on news and engage in discussions. For an analysis on IT trends, we chose Tweet data because not only it produces massive unstructured textual data in real time but also it serves as an influential channel for opinion leading on technology. Previous studies found that the tweet data provides useful information and detects the trend of society effectively, these studies also identifies that Twitter can track the issue faster than the other media, newspapers. Therefore, this study investigates how frequently the predicted IT trends for the following year announced by public organizations are mentioned on social network services like Twitter. IT trend predictions for 2013, announced near the end of 2012 from two domestic organizations, the National IT Industry Promotion Agency (NIPA) and the National Information Society Agency (NIA), were used as a basis for this research. The present study analyzes the Twitter data generated from Seoul (Korea) compared with the predictions of the two organizations to analyze the differences. Thus, Twitter data analysis requires various natural language processing techniques, including the removal of stop words, and noun extraction for processing various unrefined forms of unstructured data. To overcome these challenges, we used SAS IRS (Information Retrieval Studio) developed by SAS to capture the trend in real-time processing big stream datasets of Twitter. The system offers a framework for crawling, normalizing, analyzing, indexing and searching tweet data. As a result, we have crawled the entire Twitter sphere in Seoul area and obtained 21,589 tweets in 2013 to review how frequently the IT trend topics announced by the two organizations were mentioned by the people in Seoul. The results shows that most IT trend predicted by NIPA and NIA were all frequently mentioned in Twitter except some topics such as 'new types of security threat', 'green IT', 'next generation semiconductor' since these topics non generalized compound words so they can be mentioned in Twitter with other words. To answer whether the IT trend tweets from Korea is related to the following year's IT trends in real world, we compared Twitter's trending topics with those in Nara Market, Korea's online e-Procurement system which is a nationwide web-based procurement system, dealing with whole procurement process of all public organizations in Korea. The correlation analysis show that Tweet frequencies on IT trending topics predicted by NIPA and NIA are significantly correlated with frequencies on IT topics mentioned in project announcements by Nara market in 2012 and 2013. The main contribution of our research can be found in the following aspects: i) the IT topic predictions announced by NIPA and NIA can provide an effective guideline to IT professionals and researchers in Korea who are looking for verified IT topic trends in the following topic, ii) researchers can use Twitter to get some useful ideas to detect and predict dynamic trends of technological and social issues.

Sentiment Analysis of Movie Review Using Integrated CNN-LSTM Mode (CNN-LSTM 조합모델을 이용한 영화리뷰 감성분석)

  • Park, Ho-yeon;Kim, Kyoung-jae
    • Journal of Intelligence and Information Systems
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    • v.25 no.4
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    • pp.141-154
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    • 2019
  • Rapid growth of internet technology and social media is progressing. Data mining technology has evolved to enable unstructured document representations in a variety of applications. Sentiment analysis is an important technology that can distinguish poor or high-quality content through text data of products, and it has proliferated during text mining. Sentiment analysis mainly analyzes people's opinions in text data by assigning predefined data categories as positive and negative. This has been studied in various directions in terms of accuracy from simple rule-based to dictionary-based approaches using predefined labels. In fact, sentiment analysis is one of the most active researches in natural language processing and is widely studied in text mining. When real online reviews aren't available for others, it's not only easy to openly collect information, but it also affects your business. In marketing, real-world information from customers is gathered on websites, not surveys. Depending on whether the website's posts are positive or negative, the customer response is reflected in the sales and tries to identify the information. However, many reviews on a website are not always good, and difficult to identify. The earlier studies in this research area used the reviews data of the Amazon.com shopping mal, but the research data used in the recent studies uses the data for stock market trends, blogs, news articles, weather forecasts, IMDB, and facebook etc. However, the lack of accuracy is recognized because sentiment calculations are changed according to the subject, paragraph, sentiment lexicon direction, and sentence strength. This study aims to classify the polarity analysis of sentiment analysis into positive and negative categories and increase the prediction accuracy of the polarity analysis using the pretrained IMDB review data set. First, the text classification algorithm related to sentiment analysis adopts the popular machine learning algorithms such as NB (naive bayes), SVM (support vector machines), XGboost, RF (random forests), and Gradient Boost as comparative models. Second, deep learning has demonstrated discriminative features that can extract complex features of data. Representative algorithms are CNN (convolution neural networks), RNN (recurrent neural networks), LSTM (long-short term memory). CNN can be used similarly to BoW when processing a sentence in vector format, but does not consider sequential data attributes. RNN can handle well in order because it takes into account the time information of the data, but there is a long-term dependency on memory. To solve the problem of long-term dependence, LSTM is used. For the comparison, CNN and LSTM were chosen as simple deep learning models. In addition to classical machine learning algorithms, CNN, LSTM, and the integrated models were analyzed. Although there are many parameters for the algorithms, we examined the relationship between numerical value and precision to find the optimal combination. And, we tried to figure out how the models work well for sentiment analysis and how these models work. This study proposes integrated CNN and LSTM algorithms to extract the positive and negative features of text analysis. The reasons for mixing these two algorithms are as follows. CNN can extract features for the classification automatically by applying convolution layer and massively parallel processing. LSTM is not capable of highly parallel processing. Like faucets, the LSTM has input, output, and forget gates that can be moved and controlled at a desired time. These gates have the advantage of placing memory blocks on hidden nodes. The memory block of the LSTM may not store all the data, but it can solve the CNN's long-term dependency problem. Furthermore, when LSTM is used in CNN's pooling layer, it has an end-to-end structure, so that spatial and temporal features can be designed simultaneously. In combination with CNN-LSTM, 90.33% accuracy was measured. This is slower than CNN, but faster than LSTM. The presented model was more accurate than other models. In addition, each word embedding layer can be improved when training the kernel step by step. CNN-LSTM can improve the weakness of each model, and there is an advantage of improving the learning by layer using the end-to-end structure of LSTM. Based on these reasons, this study tries to enhance the classification accuracy of movie reviews using the integrated CNN-LSTM model.

Latent topics-based product reputation mining (잠재 토픽 기반의 제품 평판 마이닝)

  • Park, Sang-Min;On, Byung-Won
    • Journal of Intelligence and Information Systems
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    • v.23 no.2
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    • pp.39-70
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    • 2017
  • Data-drive analytics techniques have been recently applied to public surveys. Instead of simply gathering survey results or expert opinions to research the preference for a recently launched product, enterprises need a way to collect and analyze various types of online data and then accurately figure out customer preferences. In the main concept of existing data-based survey methods, the sentiment lexicon for a particular domain is first constructed by domain experts who usually judge the positive, neutral, or negative meanings of the frequently used words from the collected text documents. In order to research the preference for a particular product, the existing approach collects (1) review posts, which are related to the product, from several product review web sites; (2) extracts sentences (or phrases) in the collection after the pre-processing step such as stemming and removal of stop words is performed; (3) classifies the polarity (either positive or negative sense) of each sentence (or phrase) based on the sentiment lexicon; and (4) estimates the positive and negative ratios of the product by dividing the total numbers of the positive and negative sentences (or phrases) by the total number of the sentences (or phrases) in the collection. Furthermore, the existing approach automatically finds important sentences (or phrases) including the positive and negative meaning to/against the product. As a motivated example, given a product like Sonata made by Hyundai Motors, customers often want to see the summary note including what positive points are in the 'car design' aspect as well as what negative points are in thesame aspect. They also want to gain more useful information regarding other aspects such as 'car quality', 'car performance', and 'car service.' Such an information will enable customers to make good choice when they attempt to purchase brand-new vehicles. In addition, automobile makers will be able to figure out the preference and positive/negative points for new models on market. In the near future, the weak points of the models will be improved by the sentiment analysis. For this, the existing approach computes the sentiment score of each sentence (or phrase) and then selects top-k sentences (or phrases) with the highest positive and negative scores. However, the existing approach has several shortcomings and is limited to apply to real applications. The main disadvantages of the existing approach is as follows: (1) The main aspects (e.g., car design, quality, performance, and service) to a product (e.g., Hyundai Sonata) are not considered. Through the sentiment analysis without considering aspects, as a result, the summary note including the positive and negative ratios of the product and top-k sentences (or phrases) with the highest sentiment scores in the entire corpus is just reported to customers and car makers. This approach is not enough and main aspects of the target product need to be considered in the sentiment analysis. (2) In general, since the same word has different meanings across different domains, the sentiment lexicon which is proper to each domain needs to be constructed. The efficient way to construct the sentiment lexicon per domain is required because the sentiment lexicon construction is labor intensive and time consuming. To address the above problems, in this article, we propose a novel product reputation mining algorithm that (1) extracts topics hidden in review documents written by customers; (2) mines main aspects based on the extracted topics; (3) measures the positive and negative ratios of the product using the aspects; and (4) presents the digest in which a few important sentences with the positive and negative meanings are listed in each aspect. Unlike the existing approach, using hidden topics makes experts construct the sentimental lexicon easily and quickly. Furthermore, reinforcing topic semantics, we can improve the accuracy of the product reputation mining algorithms more largely than that of the existing approach. In the experiments, we collected large review documents to the domestic vehicles such as K5, SM5, and Avante; measured the positive and negative ratios of the three cars; showed top-k positive and negative summaries per aspect; and conducted statistical analysis. Our experimental results clearly show the effectiveness of the proposed method, compared with the existing method.

A Comparative Assessment Between LVTS of Canada and Fedwire of America as a Wholesale Electronic Payment System (미국과 캐나다의 거액전자지급결제제도 비교연구 - 미국의 Fedwire와 캐나다의 LVTS를 중심으로 -)

  • Lee, Byeong-Ryul
    • International Commerce and Information Review
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    • v.19 no.1
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    • pp.43-63
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    • 2017
  • I focused on LVTS compare with Fedwire to advance a research effects in this paper. The Fedwire Funds Service is generally used to make large-value, time-critical payments. The Federal Reserve Banks provide the Fedwire Funds Service, a real-time gross settlement system that enables participants to initiate funds transfer that are immediate, final, and irrevocable once processed. The Fedwire Funds Service is a credit transfer service. While, The LVTS(Large Value Transfer System) is the high value electronic wire system that facilitates the transfer of irrevocable payments in canadian dollars across the country. Through LVTS, funds can be transferred between participating financial institutions virtually instantaneously in a fully collateralized environment. Thus in this article, first of all, I considered features of payment system between LVTS and Fedwire. Second, I analyzed the governing structure and legal background. Third, I focused on the operational policy and risk aversion policy. Lastly, I suggested that the payment and banking system have to assume, with good reason, more efficiently accurately and securely operation together with conclusion.

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An Empirical Test of the Dynamic Optimality Condition for Exhaustible Resources -An Input Distance Function- (투입물거리함수를 통한 고갈자원의 동태적 최적이용 여부 검증)

  • Lee, Myunghun
    • Environmental and Resource Economics Review
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    • v.15 no.4
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    • pp.673-692
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    • 2006
  • In order to test for the dynamic optimality condition for the use of nonrenewable resource, it is necessary to estimate the shadow value of the resource in situ. In the previous literatures, a time series for in situ price has been derived either as the difference between marginal revenue and marginal cost or by differentiating with respect to the quantity of ore extracted the restricted cost function in which the quantity of ore is quasi-fixed. However, not only inconsistent estimates are likely to be generated due to the nonmalleability of capital, but the estimate of marginal revenue will be affected by market power. Since firms will likely fail to minimize the cost of the reproducible inputs subject to market prices under realistic circumstances where imperfect factor markets, strikes, or government regulations are present, the shadow in situ values obtained by estimating the restricted cost function can be biased. This paper provides a valid methodology for checking the dynamic optimality condition for a nonrenewable resource by using the input distance function. Our methodology has some advantages over previous ones: only data on quantities of inputs and outputs are required; nor is the maintained hypothesis of cost minimization required; adoption of linear programming enables us to circumvent autocorrelated errors problem caused by use of time series or panel data. The dynamic optimality condition for domestic coal mining does not hold for constant discount rates ranging from 2 to 20 percent over the period 1970~1993. The dynamic optimality condition also does not hold for variable rates ranging from fourth to four times the real interest rate.

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